Abstract--This paper presents a novel method for automatically classifying consumer video clips based on their soundtracks. We use a set of 25 overlapping semantic classes, chosen ...
Nonnegative matrix tri-factorization (NMTF) is a 3-factor decomposition of a nonnegative data matrix, X USV , where factor matrices, U, S, and V , are restricted to be nonnegativ...
We propose a scene classification method, which combines two popular methods in the literature: Spatial Pyramid Matching (SPM) and probabilistic Latent Semantic Analysis (pLSA) mod...
Representing documents by vectors that are independent of language enhances machine translation and multilingual text categorization. We use discriminative training to create a pr...
The paper proposes a new shape morphometry approach to combine advanced classification techniques with geometric features in order to identify morphological abnormalities on brain...
In many Web applications, such as blog classification and newsgroup classification, labeled data are in short supply. It often happens that obtaining labeled data in a new domain ...
Probabilistic Latent Semantic Analysis (PLSA) models have been shown to provide a better model for capturing polysemy and synonymy than Latent Semantic Analysis (LSA). However, th...
An important problem in many fields is the analysis of counts data to extract meaningful latent components. Methods like Probabilistic Latent Semantic Analysis (PLSA) and Latent ...
Madhusudana V. S. Shashanka, Bhiksha Raj, Paris Sm...
Abstract. This paper investigates a new extension of the Probabilistic Latent Semantic Analysis (PLSA) model [6] for text classification where the training set is partially labeled...
Abstract. Probabilistic models with hidden variables such as probabilistic Latent Semantic Analysis (pLSA) and Latent Dirichlet Allocation (LDA) have recently become popular for so...